Machine Learning Engineer - Reinforcement Learning
Core
Building training, evaluation, and tooling systems for LLM-powered AI agents and reinforcement learning to solve autonomous supply chain challenges.
Role type
Senior Machine Learning Engineer (Reinforcement Learning & LLM Agents)
Builds
Production AI decision-making products, agent environments, and evaluation frameworks for supply chain optimization.
Domain
Supply Chain / Logistics / Applied AI
Deliverable
production ML models
Required skills
Reinforcement Learning (RL), LLM fine-tuning, reward modeling, Python, PyTorch, agent environment design, data pipeline construction, evaluation framework development
Preferred skills
Human-in-the-loop ML systems, open-ended task evaluation, supply chain domain knowledge, side projects demonstrating engineering curiosity
Technologies
Python, PyTorch, LLMs, RLHF, RLAIF
Responsibilities
Design and implement LLM-powered agent environments for supply chain decision-making; Fine-tune, adapt, and evaluate LLMs for domain-specific reasoning; Design, test, and iterate on reward functions to capture desired agent behaviors; Review LLM traces and rollouts to identify reward hacking and shortcut behaviors; Build evaluation frameworks to measure model quality and agent performance; Create data pipelines for training, fine-tuning, and human feedback collection; Develop tooling to improve team workflows for building and deploying AI-assisted systems.
Seniority
Senior, hands-on IC
